p<-park_event%>%inner_join(park,by=c("park_id"="PARKNUM"))
## Warning: Column `park_id`/`PARKNUM` joining factors with different levels,
## coercing to character vector
event<-p%>%group_by(PARK_NAME)%>%count(event_name)
listing<-event%>%group_by(PARK_NAME)%>%summarize(cnt=sum(n))
listing
## # A tibble: 497 x 2
##    PARK_NAME                           cnt
##    <fct>                             <int>
##  1 ""                                13546
##  2 101st St. Soccer Field              101
##  3 104th St. Softball Field            101
##  4 132 St Block Association Park        18
##  5 157 St Playground                   104
##  6 6BC Botanical Garden                  8
##  7 6th St and Ave B Community Garden    93
##  8 Abe Lebewohl Park                    11
##  9 Abingdon Square                      15
## 10 Aileen Ryan Rec.  Complex           609
## # … with 487 more rows
ggplot(listing,aes(PARK_NAME,cnt)) + geom_bar(stat="identity") +coord_flip()

park$PARK_NAME<-tolower(park$PARK_NAME)
park_crime$PARK<-tolower(park_crime$PARK)
crime<-park%>%inner_join(park_crime,by=c("PARK_NAME"="PARK"))
crime_2015<-crime%>%group_by(PARK_NAME)%>%filter(Year=="2015")%>%mutate(cnt=sum(MURDER+RAPE+ROBBERY+GRAND.LARCENY+GRAND.LARCENY.OF.MOTOR.VEHICLE+FELONY.ASSAULT+BURGLARY))%>%select(PARK_NAME,cnt)%>%unique()
crime_2016<-crime%>%group_by(PARK_NAME)%>%filter(Year=="2016")%>%mutate(cnt=sum(MURDER+RAPE+ROBBERY+GRAND.LARCENY+GRAND.LARCENY.OF.MOTOR.VEHICLE+FELONY.ASSAULT+BURGLARY))%>%select(PARK_NAME,cnt)%>%unique()
crime_2017<-crime%>%group_by(PARK_NAME)%>%filter(Year=="2017")%>%mutate(cnt=sum(MURDER+RAPE+ROBBERY+GRAND.LARCENY+GRAND.LARCENY.OF.MOTOR.VEHICLE+FELONY.ASSAULT+BURGLARY))%>%select(PARK_NAME,cnt)%>%unique()
crime_2018<-crime%>%group_by(PARK_NAME)%>%filter(Year=="2018")%>%mutate(cnt=sum(MURDER+RAPE+ROBBERY+GRAND.LARCENY+GRAND.LARCENY.OF.MOTOR.VEHICLE+FELONY.ASSAULT+BURGLARY))%>%select(PARK_NAME,cnt)%>%unique()
crime_2019<-crime%>%group_by(PARK_NAME)%>%filter(Year=="2019")%>%mutate(cnt=sum(MURDER+RAPE+ROBBERY+GRAND.LARCENY+GRAND.LARCENY.OF.MOTOR.VEHICLE+FELONY.ASSAULT+BURGLARY))%>%select(PARK_NAME,cnt)%>%unique()
crime_2015
## # A tibble: 1,054 x 2
## # Groups:   PARK_NAME [1,054]
##    PARK_NAME                    cnt
##    <chr>                      <int>
##  1 commodore barry park          45
##  2 pierrepont playground          0
##  3 cobble hill park               0
##  4 brooklyn heights promenade     0
##  5 trinity park                   0
##  6 brooklyn bridge park          36
##  7 golconda playground            0
##  8 walt whitman park              0
##  9 university place               0
## 10 cadman plaza park              0
## # … with 1,044 more rows
crime_2016
## # A tibble: 1,054 x 2
## # Groups:   PARK_NAME [1,054]
##    PARK_NAME                    cnt
##    <chr>                      <int>
##  1 commodore barry park          15
##  2 pierrepont playground          0
##  3 cobble hill park               0
##  4 brooklyn heights promenade     0
##  5 trinity park                   0
##  6 brooklyn bridge park          60
##  7 golconda playground            0
##  8 walt whitman park              0
##  9 university place               0
## 10 cadman plaza park              0
## # … with 1,044 more rows
crime_2017
## # A tibble: 1,054 x 2
## # Groups:   PARK_NAME [1,054]
##    PARK_NAME                    cnt
##    <chr>                      <int>
##  1 commodore barry park           0
##  2 pierrepont playground          0
##  3 cobble hill park               0
##  4 brooklyn heights promenade    11
##  5 trinity park                   0
##  6 brooklyn bridge park          76
##  7 golconda playground           14
##  8 walt whitman park              0
##  9 university place               0
## 10 cadman plaza park              4
## # … with 1,044 more rows
crime_2018
## # A tibble: 1,054 x 2
## # Groups:   PARK_NAME [1,054]
##    PARK_NAME                    cnt
##    <chr>                      <int>
##  1 commodore barry park           0
##  2 pierrepont playground          2
##  3 cobble hill park               0
##  4 brooklyn heights promenade    22
##  5 trinity park                   0
##  6 brooklyn bridge park         108
##  7 golconda playground           14
##  8 walt whitman park              0
##  9 university place               0
## 10 cadman plaza park              8
## # … with 1,044 more rows
crime_2019
## # A tibble: 1,054 x 2
## # Groups:   PARK_NAME [1,054]
##    PARK_NAME                    cnt
##    <chr>                      <int>
##  1 commodore barry park          45
##  2 pierrepont playground          0
##  3 cobble hill park               0
##  4 brooklyn heights promenade    11
##  5 trinity park                   7
##  6 brooklyn bridge park          76
##  7 golconda playground           14
##  8 walt whitman park              0
##  9 university place               0
## 10 cadman plaza park              4
## # … with 1,044 more rows
#ggplot(crime_2015%>%filter(cnt<=100&cnt!=0),aes(PARK_NAME,cnt)) + geom_bar(stat="identity") +coord_flip()
ggplot(crime_2015%>%filter(cnt!=0),aes(PARK_NAME,cnt)) + geom_bar(stat="identity") +coord_flip()

ggplot(crime_2016%>%filter(cnt!=0),aes(PARK_NAME,cnt)) + geom_bar(stat="identity") +coord_flip()

ggplot(crime_2017%>%filter(cnt!=0),aes(PARK_NAME,cnt)) + geom_bar(stat="identity") +coord_flip()

ggplot(crime_2018%>%filter(cnt!=0),aes(PARK_NAME,cnt)) + geom_bar(stat="identity") +coord_flip()

ggplot(crime_2019%>%filter(cnt!=0),aes(PARK_NAME,cnt)) + geom_bar(stat="identity") +coord_flip()